Big Data Analytics Course Training in Zurich, Switzerland

Unleash the power of Big Data by learning ways of changing big data with other frameworks

  • 30 hours of intensive training on Big Data and its frameworks
  • A complete curriculum with an extensive focus on PIG, HIVE, etc frameworks
  • Learn practical applications with case studies and hands-on exercises
  • Get a clear understanding of Hadoop Ecosystems and various integrations
  • Grasp the concepts with in-depth questionnaires on each topic with projects
Group Discount

Why Learn Big Data Analytics?

Big Data analytics is a process of gathering, managing, and analyzing the large set of data (Big Data) to find out patterns and other useful information. This technology helps to understand the information contained inside the data and also help to identify the data which is a crucial part of any business and future business decisions. This component is essential for large organizations like Facebook who manage over a billion users every day, with its billion-dollar evaluation at stake every day.

Similarly, Linkedin provides its users with millions of personalized suggestions on a regular basis. LinkedIn does it with the help of components like HDFS features and MapReduce in Big Data Analytics. From the past few years, Big Data has been spreading like a fire. Due to the present technology, today it is possible to analyze the data and find solutions from it very quickly with reduced efforts.

According to a recent McKinsey report the demand for ‘Big Data’ professionals could outpace the supply by 50 to 60 percent, and U.S.-based companies will be looking to hire over 1.5 million managers and big data analysts with a sharp knowledge of how big data can be applied. 

As the Big Data demand is soaring, companies started investing in Big Data and hiring Big data Analysts to change the landscape of many industries. IBM listed the listing for data science and analytics is expected to grow to 3,64,000 to nearly 27,20,000 by 2020. According to a recent study done by Forrester, companies only analyze about 12% data at their disposal. 88% of the data is ignored, mainly due to the lack of analytics and repressive data silos. Hence, there is a major opportunity for developers to fill the big shoes of big data analyzers and start one of the most interesting and promising career prospects.

Benefits

Big data analytics certification is growing in demand today and its certification is most relevant in data science today than most other fields. The field of data analytics is new and large sufficient professionals in the field makes it difficult even for large organizations to hire new resources. Hence, the credibility of big data analytics certification promises several opportunities of growth for organizations as well as individuals in the booming field of data science.

Many big companies like Google, Apple, Adobe, and so on are investing in Big Data. Let’s take a look at the benefits of Big Data that organizations and individuals are experiencing:

Benefits for Individuals

  • An individual with Big Data analytics skills can make decisions more effectively
  • Based on the IBM survey, the Big Data analytics job market is expected to grow by 15% in the year 2020
  • According to Glassdoor, Big Data Engineers are earning an average of $116,591 per annum
  • An individual with Big Data skills can earn a better salary, good career growth, and more chances of getting hired by top companies

Benefits for Organizations

  • Big Data let organizations understand consumer needs to get an optimized experience
  • It helps to save cost on storing a large amount of data
  • Businesses can analyze data immediately with the help of high-speed tools in Big data
  • With Big Data Analytics, organizations understand market considerations and develop products accordingly.

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What you will learn

Who should attend the Apache Storm course?

  • Data Architects
  • Data Scientists
  • Developers
  • Data Analysts
  • BI Analysts
  • BI Developers
  • SAS Developers
  • Project Managers
  • Mainframe and Analytics Professionals
  • Professionals who want to acquire knowledge on Big Data
Prerequisites

There are no specific prerequisites required to learn Big Data.

Project

Recommendation Engine

Creating Recommendation system for Online Video Channels with the Historical Data using Cubing Comparing with the Benchmark Values.

Sentimental Analytics

Creating Sentimental Analytics by Downloading the Tweets from Twitter and Feeds the trending data to the Application.

Clickstream Analytics

Performing Clickstream Analytics on the Application data and engaging Customers by Customizing the Articles to the Customer for a UK Web Based Channel.

KnowledgeHut Experience

Instructor-led Live Classroom

Interact with instructors in real-time— listen, learn, question and apply. Our instructors are industry experts and deliver hands-on learning.

Curriculum Designed by Experts

Our courseware is always current and updated with the latest tech advancements. Stay globally relevant and empower yourself with the latest training!

Learn through Doing

Learn theory backed by practical case studies, exercises, and coding practice. Get skills and knowledge that can be applied effectively.

Mentored by Industry Leaders

Learn from the best in the field. Our mentors are all experienced professionals in the fields they teach.

Advance from the Basics

Learn concepts from scratch, and advance your learning through step-by-step guidance on tools and techniques.

Code Reviews by Professionals

Get reviews and feedback on your final projects from professional developers.

Curriculum

Learning Objective:

You will get introduced to the real-world problems with Bigdata and also how to solve those problems with Modern Big Data Tools.Understand where hadoop stands in giving Solution to the Traditional Processing with its outstanding features.You will get to Know Hadoop background and different Distribution of Hadoop available in Market.Prepare the Unix Box for the training.


Topics:

1.1 Big Data Introduction

  • What is Big Data
  • Data Analytics
  • Big Data Challenges
  • Technologies supported by big data

1.2 Hadoop Introduction

  • What is Hadoop?
  • History of Hadoop
  • Basic Concepts
  • Future of Hadoop
  • The Hadoop Distributed File System
  • Anatomy of a Hadoop Cluster
  • Breakthroughs of Hadoop
  • Hadoop Distributions:
  • Apache Hadoop
  • Cloudera Hadoop
  • Horton Networks Hadoop
  • MapR Hadoop

Hands On:

Installation of Virtual Machine using VMPlayer on Host Machine. And work with Some basics Unix Commands needs for Hadoop.

Learning Objective:

You will learn what are the different Daemons and its functionality at high Level.


Topics:

  • Name Node
  • Data Node
  • Secondary Name Node
  • Job Tracker
  • Task Tracker

Hands On:

Creates a Unix Shell Script to run all the deamons at one time.

Starting HDFS and MR separately.

Learning Objective:

You will get to know how File will be Write and Read in HDFS. Understand How Name Node, Data Node and Secondary Name Node takes part in HDFS Architecture. You will also know different ways of Accessing HDFS data.


Topics:

  • Blocks and Input Splits
  • Data Replication
  • Hadoop Rack Awareness
  • Cluster Architecture and Block Placement
  • Accessing HDFS
  • JAVA Approach
  • CLI Approach

Hands On:

Writes a shell Script which write and read Files in HDFS. Changes Replication factor at three levels. Use Java for working with HDFS.

Writes different HDFS Commands and also Admin Commands.

Learning Objective:

You will learn different modes of Hadoop and also see Pseudo Mode from scratch and works with Configuration. You will learn functionality of different HDFS operation and Visually Representation of HDFS Read and Write actions with its Daemons Namenode and Data Node.


Topics:

  • Local Mode
  • Pseudo-distributed Mode
  • Fully distributed mode
  • Pseudo Mode installation and configurations
  • HDFS basic file operations

Hands On:Install Virtual Box Manager and install Hadoop in Pseudo distributed mode. Changes the different Configuration files required for Pseudo Distributed mode. Performs different File Operations on HDFS.

Learning Objective:

Understand different Phases in Map Reduce including Map, Shuffling, Sorting and Reduce Phases.Life Cycle of MR in YARN submission. Distributed Cache concept in detail with examples.Writes Wordcount MR Program and monitors the Job using Job Tracker and YARN Console. And more use cases.


Topics:

  • Basic API Concepts
  • The Driver Class
  • The Mapper Class
  • The Reducer Class
  • The Combiner Class
  • The Partitioner Class
  • Examining a Sample MapReduce Program with several examples
  • Hadoop's Streaming API

Hands On:

  • Writing MR job from scratch. Writes different Logics in Mapper and Reducer. Submits the MR Job in Standalone and Distributed mode.
  • Writing Word Count MR job .Calculating Average Salary of employee who meets certain conditions. Sales Calculation using MR.

6.1 PIG

Learning Objective:

Understand importance of Pig in Big Data World. PIG architecture and its PIG Latin commands for doing different complex operation on Relations. And also Pig UDF and Aggregation functions with piggy bank library. Learns How to pass dynamic arguments to Pig Scripts.


Topics

  • PIG concepts
  • Install and configure PIG on a cluster
  • PIG Vs MapReduce and SQL
  • Write sample PIG Latin scripts
  • Modes of running PIG
  • PIG UDFs.

Hands On:

Login to Pig Grunt shell to issue Pig Latin commands in different Execution modes. Different ways of loading and transformation on Pig relations lazily. Registering UDF in grunt shell and perform Replicated Join Operations


6.2 HIVE

Learning Objective:

Understand importance of Hive in Big Data World. Different ways of configuring HIVE Metastore. Learns different types of tables in hive. Learns how to optimize hive jobs using Partitioning and Bucketing. Passing dynamic Arguments to Hive scripts. You will learn Joins,UDFS,Views etc.

Topics:

  • Hive concepts
  • Hive architecture
  • Installing and configuring HIVE
  • Managed tables and external tables
  • Joins in HIVE
  • Multiple ways of inserting data in HIVE tables
  • CTAS, views, alter tables
  • User defined functions in HIVE
  • Hive UDF

Hands On:

    Executes Hive Queries in different Modes. Creates Internal and External tables. Perform Query Optimization by creating tables with Partition and Bucketing Concepts. Run System defined and User Define Functions including Explode and Windows Functions.


6.3 SQOOP

Learning Objectives:

Learns how to import normally and Incrementally data from RDBMS to HDFS and HIVE tables. And also learns how to export the data from HDFS and HIVE table to RDBMS.Learns Architecture of Sqoop Import and Export.

Topics:

  • SQOOP concepts
  • SQOOP architecture
  • Install and configure SQOOP
  • Connecting to RDBMS
  • Internal mechanism of import/export
  • Import data from Oracle/MySQL to HIVE
  • Export data to Oracle/MySQL
  • Other SQOOP commands.

Hands On:

Triggers Shell script to call Sqoop import and Export Commands.Automating Sqoop Incremental imports with entering the last value of the appended Column. Run Sqoop export from HIVE table directly to RDBMS.


6.4 HBASE

Learning Objectives:

Understand different types of NOSQL databases and CAP theorem. Learn different DDL and CRUD operations of HBASE. Understand Hbase Architecture and Zookeeper Importance in managing HBase. Learns Hbase Column Family optimization and client Side Buffering.

Topics:

  • HBASE concepts
  • ZOOKEEPER concepts
  • HBASE and Region server architecture
  • File storage architecture
  • NoSQL vs SQL
  • Defining Schema and basic operations
  • DDLs
  • DMLs
  • HBASE use cases

Hands On:

Create HBASE tables using Shell and perform CRUD operations with JAVA API.Changes the column family properties and also perform sharding process. And also creates tables with multiple splits to improve the performance of HBASE query.


6.5 OOZIE

Learning Objectives:

Understand Oozie Architecture and monitor Oozie Workflow using Oozie. Understands how Coordinator and Bundles work along with Workflow in Oozie. And also Learns Oozie Commands to submit, Monitors and Kill the Workflow.

Topics:

  • OOZIE concepts
  • OOZIE architecture
  • Workflow engine
  • Job coordinator
  • Installing and configuring OOZIE
  • HPDL and XML for creating Workflows
  • Nodes in OOZIE
  • Action nodes and Control nodes
  • Accessing OOZIE jobs through CLI, and web console
  • Develop and run sample workflows in OOZIE
  • Run MapReduce programs
  • Run HIVE scripts/jobs.

Hands on:

Creates the Workflow to incremental Imports of Sqoop. Creates the Workflow for Pig, Hive and Sqoop Exports. And also executes Coordinator to Schedule the Workflows.


6.6 FLUME

Learning Objectives:

Understand Flume Architecture and its components Source, Channel and Sinks. Configures flume with Socket, File Sources and HDFS and Hbase Sink. Understand Fan In and Fan Out Architecture.

Topics:

  • FLUME Concepts
  • FLUME Architecture
  • Installation and configurations
  • Executing FLUME jobs

Hands on:

Creates flume Configurations files and configures with Different Source and Sinks. Stream Twitter Data and creates hive table.

Learning Objective:You will learn Pentaho Big Data Best Practices, Guidelines, and Techniques documents.


Topics:

  • Data Analytics using Pentaho as an ETL tool
  • Big Data Integration with Zero Coding Required

Hands on:You will use Pentaho as ETL tool for data analytics.

Learning Objective:

You will see different Integrations among hadoop ecosystem in a Data engineering Flow. And also understand how important it is to create a flow for ETL process.


Topics:

  • MapReduce and HIVE integration
  • MapReduce and HBASE integration
  • Java and HIVE integration
  • HIVE - HBASE Integration

Hands On:Uses Storage Handlers for integrating HIVE and HBASE. Integrates HIVE and PIG as well.

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FAQs

Big Data Analytics Course

There are no prerequisites for attending this course.

Big Data analytics is important for companies and individuals to utilise data in the most efficient manner to cut costs.

the high frequency of tools such as Hadoop can help identify new sources of Data to help businesses to make quick decisions, To understand market trends and develop new products

  • Fresher’s Who Would like to build the carrier in the Distributed World, this is an introductory course.
  • Laterals which want to learn Framework like SPARK, Hadoop Knowledge Will add benefit.
  • Software Developers and Architects
  • Analytics Professionals
  • Senior IT professionals
  • Testing and Mainframe professionals
  • Data Management Professionals
  • Business Intelligence Professionals
  • Project Managers
  • Aspiring Data Scientists
  • Graduates looking to build a career in Big Data Analytics

RAM: Minimum - 8 GB Recommended - 16GB DDR4

Hard Disk Space: 40 GB Recommended - 256 GB

Processor: i3 and above

  • Understanding the Core Concepts of Hadoop which includes Hadoop Distributed File System (HDFS) and Map-Reduce(MR)
  • Understanding NO-SQL databases like HBASE and CASSANDRA.
  • Understanding Hadoop Ecosystem like HIVE, PIG,SQOOP and FLUME
  • Acquiring knowledge in other aspects like scheduling Hadoop jobs using Python, R, Ruby. Etc.
  • Developing Batch Analytics applications for UK Web Based News Channels to Up cast the News and Engaging customer with the Customized Recommendations.
  • Integrating Clickstream and Sentimental Analytics to the UK Web Based News Channel.
  • HADOOP COURSE IS DIVIDED INTO FIVE PHASES.
  • Ingestion Phase(FLUME AND SQOOP),Storage Phase(HDFS and HBASE),Processing Phase(MR, HIVE, PIG and SPARK), Cluster Management(Standalone and YARN) and Integrations(HCATALOG, ZOOKEEPER and OOZIE)
  • Accelerated career growth.
  • Increased pay package due to Hadoop skills.

The Big Data Analytics training does not have any restrictions although participants would benefit slightly if they’re familiar with basic programming languages.

Workshop Experience

All of the training programs conducted by us are interactive in nature and fun to learn as a great amount of time is spent on hands-on practical training, use case discussions, and quizzes. An extensive set of collaborative tools and techniques are used by our trainers which will improve your online training experience.

The Big Data Analytics training conducted at KnowledgeHut is customized according to the preferences of the learner. The training is conducted in three ways:

Online Classroom training: You can learn from anywhere through the most preferred virtual live and interactive training

Self-paced learning: This way of learning will provide you lifetime access to high-quality, self-paced e-learning materials designed by our team of industry experts

Team/Corporate Training: In this type of training, a company can either pick an employee or entire team to take online or classroom training. Flexible pricing options, standard Learning Management System (LMS), and enterprise dashboard are the add-on features of this training. Moreover, you can customize your curriculum based on your learning needs and also get post-training support from the expert during your real-time project implementation.

The sessions that are conducted are 30 hours of live sessions, with 15 hours MCQs and 8 hours of Assignments and 20 hours of hands-on sessions.

Course Duration information:

Online training:

  • Duration of 15 sessions.
  • 2 hour per day.

Weekend training:

  • Duration of 5 Weekends.
  • Class held 2 days per week on Saturday, Sunday.
  • Note: Each session of 3 hours.

Yes, our lab facility at KnowledgeHut has the latest version of hardware and software and is very well-equipped. We provide Cloudlabs so that you can get a hands-on experience of the features of Big Data Analytics. Cloudlabs provides you with real-world scenarios can practice from anywhere around the globe. You will have an opportunity to have live hands-on coding sessions. Moreover, you will be given practice assignments to work on after your class.

Here at KnowledgeHut, we have Cloudlabs for all major categories like cloud computing, web development, and Data Science.

This Big Data Analytics training course have three projects, viz Recommendation Engine, Sentimental Analytics, Clickstream Analytics

  • Recommendation Engine: Creating Recommendation system for Online Video Channels with the Historical Data using Cubing Comparing with the Benchmark Values.
  • Sentimental Analytics: Creating Sentimental Analytics by Downloading the Tweets from Twitter and Feeds the trending data to the Application.
  • Clickstream Analytics: Performing Clickstream Analytics on the Application data and engaging Customers by Customizing the Articles to the Customer for a UK Web Based Channel

VMWare workstation or player [Depending on the OS]

The Image for Hadoop - 2.7.2 and Pig

Winscp or FileZilla [ Depending on OS ]

Putty or a simple console [ Depending on OS ]

The Learning Management System (LMS) provides you with everything that you need to complete your projects, such as the data points and problem statements. If you are still facing any problems, feel free to contact us.

After the completion of your course, you will be submitting your project to the trainer. The trainer will be evaluating your project. After a complete evaluation of the project and completion of your online exam, you will be certified a Big Data Analyst.

Online Experience

We provide our students with Environment/Server access for their systems. This ensures that every student experiences a real-time experience as it offers all the facilities required to get a detailed understanding of the course.

If you get any queries during the process or the course, you can reach out to our support team.

The trainer who will be conducting our Big Data Analytics certification has comprehensive experience in developing and delivering Big Data applications. He has years of experience in training professionals in Big Data. Our coaches are very motivating and encouraging, as well as provide a friendly learning environment for the students who are keen about learning and making a leap in their career.

Yes, you can attend a demo session before getting yourself enrolled for the Big Data Analytics training.

All our Online instructor-led training is an interactive session. Any point of time during the session you can unmute yourself and ask the doubts/ queries related to the course topics.

There are very few chances of you missing any of the Big Data Analytics training session at KnowledgeHut. But in case you miss any lecture, you have two options:

  • You can watch the online recording of the session
  • You can attend the missed class in any other live batch.

The online Apache Spark course recordings will be available to you with lifetime validity.

Yes, the students will be able to access the coursework anytime even after the completion of their course.

Opting for online training is more convenient than classroom training, adding quality to the training mode. Our online students will have someone to help them any time of the day, even after the class ends. This makes sure that people or students are meeting their end learning objectives. Moreover, we provide our learners with lifetime access to our updated course materials.

In an online classroom, students can log in at the scheduled time to a live learning environment which is led by an instructor. You can interact, communicate, view and discuss presentations, and engage with learning resources while working in groups, all in an online setting. Our instructors use an extensive set of collaboration tools and techniques which improves your online training experience.

This will be live interactive training led by an instructor in a virtual classroom.

We have a team of dedicated professionals known for their keen enthusiasm. As long as you have a will to learn, our team will support you in every step. In case of any queries, you can reach out to our 24/7 dedicated support at any of the numbers provided in the link below: https://www.knowledgehut.com/contact-us

We also have Slack workspace for the corporates to discuss the issues. If the query is not resolved by email, then we will facilitate a one-on-one discussion session with one of our trainers.

Finance Related

We accept the following payment options:

  • PayPal
  • American Express
  • Citrus
  • MasterCard
  • Visa

KnowledgeHut offers a 100% money back guarantee if the candidates withdraw from the course right after the first session. To learn more about the 100% refund policy, visit our refund page.

If you find it difficult to cope, you may discontinue within the first 48 hours of registration and avail a 100% refund (please note that all cancellations will incur a 5% reduction in the refunded amount due to transactional costs applicable while refunding). Refunds will be processed within 30 days of receipt of a written request for refund. Learn more about our refund policy here.

Typically, KnowledgeHut’s training is exhaustive and the mentors will help you in understanding the concepts in-depth.

However, if you find it difficult to cope, you may discontinue and withdraw from the course right after the first session as well as avail 100% money back.  To learn more about the 100% refund policy, visit our Refund Policy.

Yes, we have scholarships available for Students and Veterans. We do provide grants that can vary up to 50% of the course fees.

To avail scholarships, feel free to get in touch with us at the following link: https://www.knowledgehut.com/contact-us

The team shall send across the forms and instructions to you. Based on the responses and answers that we receive, the panel of experts takes a decision on the Grant. The entire process could take around 7 to 15 days

Yes, you can pay the course fee in installments. To avail, please get in touch with us at https://www.knowledgehut.com/contact-us. Our team will brief you on the process of installment process and the timeline for your case.

Mostly the installments vary from 2 to 3 but have to be fully paid before the completion of the course.

Visit the following page to register yourself for the Big Data Analytics Training: https://www.knowledgehut.com/big-data/big-data-analytics-training/schedule/

You can check the schedule of the Big Data Analytics Training by visiting the following link: https://www.knowledgehut.com/big-data/big-data-analytics-training/schedule/

We have a team of dedicated professionals known for their keen enthusiasm. As long as you have a will to learn, our team will support you in every step. In case of any queries, you can reach out to our 24/7 dedicated support at any of the numbers provided in the link below: https://www.knowledgehut.com/contact-us

We also have Slack workspace for the corporates to discuss the issues. If the query is not resolved by email, then we will facilitate a one-on-one discussion session with one of our trainers.

Yes, there will be other participants for all the online public workshops and would be logging in from different locations. Learning with different people will be an added advantage for you which will help you fill the knowledge gap and increase your network.

Have More Questions?

Big Data Analytics Course Course in Zurich

Zurich, a globally acclaimed European city is famous for its natural beauty and scenic tourist spots. This city is not only blessed with natural wonders but also has a prosperous economy thanks to the booming IT, financial industries. The easy availability of resources and numerous recreational activities have made Zurich the ideal location for corporations across the world to have their offices. Professionals who wish to have a prosperous career in Zurich find it easy to get the desired job when they are equipped with certification and training in various technologies. For such professionals KnowledgeHut provides various training and courses so that individuals can update their skill-set and hone their capabilities. The Big Data Analytics online classes from KnowledgeHut are a useful training for professionals in the data analysis and processing sector. This program offers complete knowledge and learning in data analysis sector. Why Big Data Analytics Big Data Analytics is an effective tool for managing and processing data. By using this system, organizations are able to arrange and categorize large amounts of data effectively. This system, through its systematic approach, reduces time, cost and other resources and helps in enhancing productivity. Thus, achieving diverse goals becomes convenient and companies can actually find out their problem areas and find solutions accordingly. This system is also instrumental in understanding the patterns and trends in data and highlights the vital issues. Adopting Big Data Analytics is simple and it can be utilized for various purposes. Benefits of this Course The Big Data Analytics course in Zurich hones your analytical and problem solving skills and enables you to attain mastery over the various techniques and strategies of Data evaluation. After completing this course you will have the credibility and expertise to arrange and segregate data systematically. This program also teaches you the numerous ways of transforming data which makes it easier to analyze. Thus, by completing this training, your career gets a boost and it becomes easy to get your dream job. The learning from the Big Data Analytics certification in Zurich keeps you ahead of the curve and gives you a distinctive edge over your peers. With the help of this learning you can also prepare for an exam related to this work domain. Advantage KnowledgeHut With online training facilities like online classes and online training, KnowledgeHut makes it easier for professionals with time constrains to pursue the Big Data Analytics training online in Zurich. These e-learning facilities along with highly experienced trainers make the learning process smooth and help in understanding the course content. KnowledgeHut charges a reasonable price for Big Data Analytics courses in Zurich and hence, it is the ideal choice for this program.